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Sequential Recommendation

Sequential recommendation is a sophisticated approach to providing personalized suggestions by analyzing users' historical interactions in a sequential manner. Unlike traditional recommendation systems, which consider items in isolation, sequential recommendation takes into account the temporal order of user actions. This method is particularly valuable in domains where the sequence of events matters, such as streaming services, e-commerce platforms, and social media.

Papers

Showing 511520 of 554 papers

TitleStatusHype
Sequential Recommendation with Self-Attentive Multi-Adversarial NetworkCode1
Controllable Multi-Interest Framework for RecommendationCode1
Inter-sequence Enhanced Framework for Personalized Sequential Recommendation0
A Generic Network Compression Framework for Sequential Recommender SystemsCode1
CSRN: Collaborative Sequential Recommendation Networks for News Retrieval0
HAM: Hybrid Associations Models for Sequential RecommendationCode0
Advances in Collaborative Filtering and RankingCode1
Learning to Structure Long-term Dependence for Sequential Recommendation0
Déjà vu: A Contextualized Temporal Attention Mechanism for Sequential Recommendation0
SANST: A Self-Attentive Network for Next Point-of-Interest Recommendation0
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